adding hist and kaplan meier to

acro.R

@@ -1,6 +1,7 @@
 library(reticulate)  # import Python modules
 library(admiraldev)
-library(stringr)
+library(png)
+library(grid)
 
 acro <- import("acro")
 ac <- acro$ACRO()
@@ -17,32 +18,32 @@ acro_table <- function(index, columns, dnn=NULL, deparse.level=0, ...)
     "ACRO crosstab without aggregation function"
     if (is.null(dnn)) {
         if (deparse.level == 0) {
-        rownames <- list("")
-        colnames <- list("")
+        row_names <- list("")
+        col_names <- list("")
         } else if (deparse.level == 1) {
             tryCatch({
                 index_symbol <- assert_symbol(substitute(index))
-                rownames <- list(deparse(index_symbol))},
+                row_names <- list(deparse(index_symbol))},
                 error = function(e) {
-                    rownames <<- list("")
+                    row_names <- list("")
             })
             tryCatch({
                 column_symbol <- assert_symbol(substitute(columns))
-                colnames <- list(deparse(column_symbol))},
+                col_names <- list(deparse(column_symbol))},
                 error = function(e) {
-                    colnames <<- list("")
+                    col_names <- list("")
             })
         } else if (deparse.level == 2) {
-            rownames <- list(deparse((substitute(index))))
-            colnames <- list(deparse(substitute(columns)))
+            row_names <- list(deparse((substitute(index))))
+            col_names <- list(deparse(substitute(columns)))
         }
     }
     else {
-        rownames <- list(dnn[1])
-        colnames <- list(dnn[2])
+        row_names <- list(dnn[1])
+        col_names <- list(dnn[2])
     }
 
-    table <- ac$crosstab(index, columns, rownames=rownames, colnames=colnames)
+    table <- ac$crosstab(index, columns, rownames=row_names, colnames=col_names)
     # Check for any unused arguments
       if (length(list(...)) > 0) {
         warning("Unused arguments were provided: ", paste0(names(list(...)), collapse = ", "), "\n", "To find more help about the function use: acro_help(\"acro_table\")\n")
@@ -77,6 +78,24 @@ acro_glm <- function(formula, data, family)
     model$summary()
 }
 
+acro_hist <- function(data, column, breaks=10, freq=TRUE, col=NULL, filename="histogram.png"){
+    "ACRO histogram"
+    histogram = ac$hist(data=data, column=column, bins=breaks, density=freq, color=col, filename=filename)
+    # Load the saved histogram
+    image <- readPNG(histogram)
+    grid.raster(image)
+}
+
+acro_surv_func <- function(time, status, output, filename="kaplan-meier.png"){
+    "Estimates the survival function. Produce either a plot of table"
+    results = ac$surv_func(time=time, status=status, output=output, filename=filename)
+    if (output=="plot"){
+        # Loasd the saved survival plot
+        image <- readPNG(results[[2]])
+        grid.raster(image)
+        }
+}
+
 acro_rename_output <- function(old, new)
 {
     "Rename an output"

acro/acro_tables.py

@@ -474,10 +474,10 @@ def surv_func(  # pylint: disable=too-many-arguments,too-many-locals
             )
             return table
         if output == "plot":
-            plot = self.survival_plot(
+            plot, filename = self.survival_plot(
                 survival_table, survival_func, filename, status, sdc, command, summary
             )
-            return plot
+            return (plot, filename)
         return None
 
     def survival_table(  # pylint: disable=too-many-arguments,too-many-locals
@@ -513,7 +513,22 @@ def survival_plot(  # pylint: disable=too-many-arguments,too-many-locals
             logger.debug("Directory acro_artifacts created successfully")
         except FileExistsError:  # pragma: no cover
             logger.debug("Directory acro_artifacts already exists")
-        plt.savefig(f"acro_artifacts/{filename}")
+
+        # create a unique filename with number to avoid overwrite
+        filename, extension = os.path.splitext(filename)
+        if not extension:  # pragma: no cover
+            logger.info("Please provide a valid file extension")
+            return
+        increment_number = 0
+        while os.path.exists(
+            f"acro_artifacts/{filename}_{increment_number}{extension}"
+        ):
+            increment_number += 1
+        unique_filename = f"acro_artifacts/{filename}_{increment_number}{extension}"
+
+        # save the plot to the acro artifacts directory
+        plt.savefig(unique_filename)
+
         # record output
         self.results.add(
             status=status,
@@ -523,9 +538,9 @@ def survival_plot(  # pylint: disable=too-many-arguments,too-many-locals
             command=command,
             summary=summary,
             outcome=pd.DataFrame(),
-            output=[os.path.normpath(filename)],
+            output=[os.path.normpath(unique_filename)],
         )
-        return plot
+        return (plot, unique_filename)
 
     def hist(  # pylint: disable=too-many-arguments,too-many-locals
         self,
@@ -606,6 +621,9 @@ def hist(  # pylint: disable=too-many-arguments,too-many-locals
         Returns
         -------
         matplotlib.Axes
+            The histogram.
+        str
+            The name of the file where the histogram is saved.
         """
         logger.debug("hist()")
         command: str = utils.get_command("hist()", stack())
@@ -715,6 +733,7 @@ def hist(  # pylint: disable=too-many-arguments,too-many-locals
             outcome=pd.DataFrame(),
             output=[os.path.normpath(unique_filename)],
         )
+        return unique_filename
 
 
 def create_crosstab_masks(  # pylint: disable=too-many-arguments,too-many-locals

notebooks/test-nursery.Rmd

@@ -7,6 +7,7 @@ output: html_notebook
 # install.packages("haven")
 # install.packages("reticulate")
 # install.packages("farff")
+# install.packages("survival")
 ```
 
 ## Import Libraries
@@ -67,7 +68,7 @@ table
 index = data[, c("recommend")]
 columns = data[, c("parents")]
 
-table = acro_table(data[, c("recommend")], columns, dnn=c("rows", "columns"), deparse.level = 1, useNa = "no")
+table = acro_table(index, columns, dnn= c("recommend", "parents"), deparse.level=0)
 ```
 
 ```{r}
@@ -94,6 +95,25 @@ table = acro_pivot_table(data, values=values, index=index, aggfunc=aggfunc)
 table
 ```
 
+### ACRO histogram
+
+```{r}
+acro_hist(data, "children")
+```
+
+### ACRO survival analysis
+
+```{r}
+data(package = "survival")
+
+# Load the lung dataset
+data(lung)
+#head(lung)
+
+acro_surv_func(time=lung$time, status=lung$status, output ="plot")
+```
+```
+
 # Regression examples using ACRO
 
 Again there is an industry-standard package in python, this time called **statsmodels**.